Image or video quality is a characteristic of an image or video that is characterized by the perceived image degradation (typically, compared to an ideal image or video). Systems, such as imaging systems or streaming video systems, often introduce some amounts of distortion or artifacts on an image or video (including three-dimensional images or videos), making them less pleasurable to view or harder to interpret, hence quality assessment is an important problem.
The quality of the image/video may be assessed either by conducting subjective experiments or by developing objective image quality assessment (IQA) algorithms. Conducting subjective experiments is very difficult and does not produce a real time solution. Hence, many objective IQA algorithms that produce quality predictions that correlate well with subjective ratings have been developed. One type of IQA algorithm is a reference algorithm, such as a full reference (FR) algorithm, which assesses the quality of a test image/video by comparing it against a reference image/video that is presumed to have acceptable (high) quality. Another type of reference algorithm is a reduced reference (RR) algorithm, which assesses the quality of a test image/video with only partial information about a reference image/video that is presumed to have acceptable quality. Another type of IQA algorithm is a no-reference (NR) algorithm, which assesses the quality of a test image/video without any reference to any original one. Such an original may not exist.
Currently, many image/video systems assess the quality of an image/video via a reference algorithm, such as via an FR algorithm, as the image/video is processed (e.g., compressed) or afterwards, such as in streaming video systems. However, if the image or video content being processed was not of sufficiently high quality prior to processing, then the reference algorithm may yield incorrect measurements of the image or video quality. Comparing a possibly distorted image or video against a reference image or video that is distorted leaves poor basis for comparison.